Traditionally, therapies/treatments are based on single clinical tests and measurement devices to diagnose disease or ailment. For the most part, the intent in using such tests and devices is to obtain a single, quality measurement. Such a measurement provides a snap-shot. However, a series of measurements is required in order to understand the system dynamics and the underlying system characteristics of the disease.
A series of measurements clearly results in more data. However, it is not always easy to translate such data into actionable information. In fact, it is a far from trivial task to identify what problems can be tackled and what prerequisites are needed so as to make the more abundant data provided by continuous or frequent measurement useful in the practice of medicine. In addition, pharmaceutical companies perform the task of characterizing the metabolic activity of the drug and determining drug dosage schema. In general, pharmaceutical companies perform elaborate clinical trials to determine drug potency and drug efficacy for a target population. But strictly speaking, both pharmacokinetics and pharmacodynamics for a drug is patient specific. A population based approach is not ideally suited for determining medication for ailments such as diabetic patients where insulin drug is used on daily basis due to the variability of such a chronic disease. In such cases, the dosing schema is normally fine-tuned by practicing healthcare professionals starting from given guidelines. Typically, a healthcare provider, with the help of the patient, follows a controlled monitoring and insulin dosage adjustment scheme.
The most prevalent forms of diabetes are due to decreased production of insulin (Type 1 Diabetes Mellitus, the first recognized form), or decreased sensitivity of body tissues to insulin (Type 2 Diabetes Mellitus, the more common form). Treatment of the former requires insulin injections, while the latter is generally managed with oral medication and only requires insulin if the oral medications are ineffective. Other health problems that accelerate the damaging effects of diabetes are smoking, elevated cholesterol levels, obesity, high blood pressure, and lack of regular exercise. Accordingly, patient understanding and participation in treatment is vital since blood glucose levels change continuously.
Controlling glucose is the best method for slowing the damaging effect of glucose on organs. Conventional therapy (CT), intensive conventional therapy (ICT), and intensive conventional therapy for pump users (CSII) are common approaches used to control glucose. A limitation of such therapy approaches is that they do not make use of tools that account for patient-specific factors such as physiological variability, metabolic differences, and the effects of stress, exercise, sickness, and meals.
Glucose concentration is the primary parameter that is normally measured for euglycemic control (e.g., in order to provide a normal level of glucose in the blood). Other available information for determining better treatment concerns the metabolic loads resulting from various activities such as ingesting meals, performing physical activity, work-related stress, and so forth. Insulin delivery, other medications, and so forth are further regulating mechanisms for the targeted physiological parameter. The therapy rules are defined in terms of glucose measurements, insulin sensitivity, insulin-to-carbohydrate ratio, basal insulin rate, and other factors such as stress level and the effect of exercise. Except for the glucose measurements, current approaches determine the parameters based on rules of thumb, empirical rules, and iterative assessments based on glucose measurements.
In view of the above, there is a serious shortcoming in the current clinical approaches to addressing the needs of a diabetic patient in day-to-day life. No single solution has integrated the varied approaches available. The methods offered to date do not directly assess patient-specific needs; rather, specifics are addressed over a period of time through trial and error. In addition, simply integrating the various approaches available in the art would not accomplish the desired effect. There are specific elements for each of the methods that have to developed and tuned for the overall process to work with the desired level of safety, accuracy, and robustness. In addition, it is desirable to provide health care practitioners with tools for collecting patient-specific information over time and applying the collected information to dynamic, patient-specific models when designing therapies for such chronic illnesses and/or diseases.